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Optimising Self Adaptive Networks by Evolving RuleBased Agents  (Make Corrections)  
Evaggelos Nonas and Alexandra Poulovassilis Department of Computer Science,...



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Abstract: . The need for networks that adapt autonomously to dynamic environments is apparent. In this paper we describe how self adaptive networks can be optimised by means of agents residing on the nodes of the network. The knowledge of these agents is a set of active rules. A genetic algorithm dynamically prioritises these rules in the face of dynamically evolving conditions. To our knowledge, this is the first time that GAs have been used for this purpose. We demonstrate the applicability of... (Update)

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BibTeX entry:   (Update)

@misc{ and-optimising,
  author = "Evaggelos Nonas And",
  title = "Optimising Self Adaptive Networks by Evolving RuleBased Agents",
  url = "citeseer.ist.psu.edu/314996.html" }
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39   The active database management system manifesto: A rulebase .. - Dittrich, Gatziu et al. - 1995  DBLP
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18   A pragmatic BDI architecture (context) - Fischer, Muller et al. - 1996  DBLP
10   Designing good pursuit problems as testbeds for distributed .. (context) - Manela, Campbell - 1995  DBLP
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4   Enriching active databases with agent technology (context) - van den Akker, Siebes - 1997  ACM   DBLP

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